协同数据链的高精度时间同步设计

鉴于Link16中的RTT时间同步精度为百纳秒级别，针对其精度不高和需要GPS进行初始粗同步的缺点，本文分析了双向比对时间同步的各误差项，给出了各项误差消除或减小方法，最终能实现优于10 ns的时间同步精度，并首次提出不需要其它导航源进行初始粗同步的自主RTT算法。最后，在协同数据链动态自组织组网的需求下，对动态时隙分配时的RTT算法进行了分析，计算出对基准频率源的准确度要求，保证了改进算法在动态时隙分配时也能达到10 ns的精度。     

一种高精度的X射线脉冲星导航TOA估计方法

针对X射线脉冲星导航（XPNAV）系统的基本观测量--脉冲到达时间（TOA）的估计问题,提出一种高精度的TOA估计方法。该方法基于特征子空间分解类算法的高精度的参数估计特性,首先通过细致分析标准轮廓与折叠轮廓之间的互相关结果,构造新的观测方程;然后对该方程进行特征值分解得到两个相互正交的特征矢量;最后利用两个特征矢量之间的正交性完成TOA估计。数值仿真结果有效校验了算法的性能。     

基于TP的伽利略搜救信号参数估计算法

针对伽利略搜救系统信标信息提取时对FOA、信息位宽和TOA的高精度估计要求,考虑到用户信息未知,提出基于TP(纯载波和位帧同步信息)的多维联合极大似然估计算法和体积重心算法相结合的FOA、信息位宽、TOA估计算法。推导算法原理,并根据参数之间的相关性将估计过程分为两步完成。Monte Carlo仿真和实测结果表明,在34.8dBHz的处理门限下,FOA、信息位宽、TOA估计的均方根误差分别小于0.14Hz、2.5μs和30μs,优于其他算法估计性能,为信标信息提取提供了保障。该算法目前已应用于伽利略MEOLUT地面站。     

Distributed satellite autonomous navigation using X-ray pulsars

Distributed X-ray pulsar-based navigation (DXNAV) is an effective method to realize earth-orbit satellite positioning under weak pulsar signal conditions. In this paper, we propose a new DXNAV method based on multiple information fusion. The DXNAV system principle and the pulse phase estimate Cramér-Rao lower bound are deduced. To suppress the calculation complexity and the error source, the X-ray pulsar photon time-of-arrival detected by each satellite is equivalently converted to the leading satellite directly using the inter-satellite link ranging and starlight angular distance measurement. A high precision estimate model of the pulse phase is built using pulsar standard profile, observed profile, and star-geocentric angular distance from distributed satellites. The estimated pulse phase is real-time supplied to the navigation system, which is established in the form of a deviation equation. The two-stage Kalman filter is designed to estimate the pulse phase in profile histogram bin step and the leader position in real-time step. Compared separately with the maximum likelihood phase estimate method and the celestial navigation method using only the star-geocentric angular distance, the simulation analysis shows that the estimation precisions of position and velocity are improved by 29% and 25%.